Evidence map›Paper›PMID 29926169›Full record

ArticlePsychological research2020

Performance-informed EEG analysis reveals mixed evidence for EEG signatures unique to the processing of time.

Nadine Schlichting, Ritske de Jong, Hedderik van Rijn

Abstract read
In one paragraph

Article in Psychological research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nadine SchlichtingDepartment of Experimental Psychology, University of Groningen, Groningen, The Netherlands. n.schlichting@rug.nl.ORCID http://orcid.org/0000-0001-6068-9573
Ritske de JongDepartment of Experimental Psychology, University of Groningen, Groningen, The Netherlands.
Hedderik van RijnDepartment of Experimental Psychology, University of Groningen, Groningen, The Netherlands.

Funding

EU Horizon 2020 FET Proactive grant TIMESTORM 641100Netherlands Organisation for Scientific Research (NWO) 453-16-005
6 · The paper itself

Abstract

Certain EEG components (e.g., the contingent negative variation, CNV, or beta oscillations) have been linked to the perception of temporal magnitudes specifically. However, it is as of yet unclear whether these EEG components are really unique to time perception or reflect the perception of magnitudes in general. In the current study we recorded EEG while participants had to make judgments about duration (time condition) or numerosity (number condition) in a comparison task. This design allowed us to directly compare EEG signals between the processing of time and number. Stimuli consisted of a series of blue dots appearing and disappearing dynamically on a black screen. Each stimulus was characterized by its duration and the total number of dots that it consisted of. Because it is known that tasks like these elicit perceptual interference effects that we used a maximum-likelihood estimation (MLE) procedure to determine, for each participant and dimension separately, to what extent time and numerosity information were taken into account when making a judgement in an extensive post hoc analysis. This approach enabled us to capture individual differences in behavioral performance and, based on the MLE estimates, to select a subset of participants who suppressed task-irrelevant information. Even for this subset of participants, who showed no or only small interference effects and thus were thought to truly process temporal information in the time condition and numerosity information in the number condition, we found CNV patterns in the time-domain EEG signals for both tasks that was more pronounced in the time-task. We found no substantial evidence for differences between the processing of temporal and numerical information in the time-frequency domain.

Indexed as

IndividualityAdolescentAdultBrainElectroencephalographyFemaleHumansJudgmentMaleTime PerceptionYoung Adult

Identifiers

PMID29926169
PMCPMC7039843

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.